1. Field of the Invention
The present invention relates to a method for segmentation-based recognizing handwritten touching numeral strings, and more particularly, to a method of segmenting touching numeral strings contained in handwritten touching numeral strings, and recognizing the numeral strings by use of feature information and recognized results provided by inherent structure of digits.
2. Background of the Related Art
Recognition of handwritten numeral strings is one of pattern recognizing fields which have been most actively researched, because of having various application field such as zip codes recognition, check recognition, format document recognition or the like. A typical method of recognizing handwritten touching numeral strings is executed by a following process. Firstly, after the handwritten numerals are scanned, candidate segmentation points are determined. Strokes are obtained from the candidate segmentation points. After the obtained stroke are aggregated and recognized, the aggregation of the strokes with the highest recognition result value is set as the results of recognizing numeral string. It is difficult to segment the handwritten numeral strings by use of a character width used in the typical print character segmenting method, because of having the variety of writing forms and writing paraphernalia contrary to the print character. In addition, the segmented separate numerals in the touching numeral strings may exhibit a structural feature having a different stroke width due to the segmentation of the overlapped numeral string, contrary to the independent separate numerals contained in the numeral strings, so that it is difficult to normally segment the touching numeral strings based on the only recognized results. However, the touching numeral string contained in the handwritten numeral strings is a major factor of the error recognition in the recognition of the handwritten numeral string. Furthermore, in case of no having preliminary knowledge on the length of the touching numeral string, it is more difficult to recognize the touching numeral string. Accordingly, it is very difficult to segment and recognize the touching numeral string from the handwritten numeral strings. In addition, it is appeared that the recognized results are low relative to the recognized results of numeral strings consisting of only independent separate numerals.
In order to overcome the above drawbacks, several methods have been proposed. According to one method, candidate segmentation points are obtained from the touching numeral string, and the strokes extracted from the segmentation points are aggregated, thereby regarding the strokes with the excellent recognized results. Meanwhile, according to another method, the touching numeral strings are not segmented, but global numeral strings are recognized. The former prior art proposes an off-line recognition system for recognizing the handwritten numeral strings contained in the touching numerals and separate numerals. The system is consisting of four major modules of pre-segmentation, digit detection, segmentation-free, and global decision. The pre-segmentation module divides the input numeral strings into independent groups of numerals. The digit detection module recognizes the numeral groups containing separate numerals. The segmentation-free module segments and recognizes the touching numeral groups containing arbitrary numerals. The global decision module integrates the results of all modules, and determines the acceptance or rejection of the results. The touching numeral strings are recognized through a next step. Potential splitting points are obtained to segment the touching numeral strings. The segmentation point is obtained from the session image, and the potential splitting points comprise a singular point, an end point, a T-joint, and a crossing point. Firstly, the singular point is searched in the session image of the touching numeral strings, and then is eliminated. Very small connecting components which are resulted from after eliminating the singular point are eliminated. After labeling the remaining connecting components, the session image is extended by a stroke width of the original touching numeral string image. The strokes obtained by the above method are aggregated, and the aggregated strokes are recognized. The aggregations of the strokes with the largest width are accepted as the recognized results. The method extracts the strokes from the touching numeral strings by use of feature segmentation points to recognize the touching numeral strings, and aggregates the strokes depending upon the recognized results. The more a length of the numeral strings is long, the more the number of the strings to be aggregated is increased. Therefore, in order to obtain the final recognized results, the more calculating amount is required. Error recognition may be happened in the aggregation of the strings depending upon the highest recognition result value among the recognized results of the aggregated strings. The above method has a drawback in that the more a length of the numeral strings is long, the more the error recognizing rate is increased.
According to another prior art, a method for segmenting one character in print character strings is proposed. The method for segmenting the character by use of a character width in the print character strings is unsuitable for the handwritten forms provided by various writing paraphernalia.